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Image Clustering On Mnist Full

Métriques

Accuracy

NMI

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Accuracy	NMI	Paper Title	Repository
VMM	0.967	0.920	The VampPrior Mixture Model	-
Tree-SNE	-	0.864	Tree-SNE: Hierarchical Clustering and Visualization Using t-SNE	-
DEN	0.984	0.956	Interpretable Visualizations with Differentiating Embedding Networks	-
SR-K-means	-	0.913	Deep clustering: On the link between discriminative models and K-means	-
DBC	0.976	0.937	Discriminatively Boosted Image Clustering with Fully Convolutional Auto-Encoders	-
DDC-DA	0.986	0.961	Deep Density-based Image Clustering	-
PSSC	0.964	0.921	Scattering Transform Based Image Clustering using Projection onto Orthogonal Complement	-
SPC	0.992	0.975	Selective Pseudo-label Clustering	-
N2D (UMAP)	0.987	0.964	N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding	-
JULE-RC	0.964	0.917	Joint Unsupervised Learning of Deep Representations and Image Clusters	-
DTI-Clustering	0.979	0.942	Deep Transformation-Invariant Clustering	-
DynAE	0.987	0.964	Deep Clustering with a Dynamic Autoencoder: From Reconstruction towards Centroids Construction	-
ClusterGAN	0.973	0.940	Balanced Self-Paced Learning for Generative Adversarial Clustering Network	-
ADEC	0.990	0.971	Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift	-
GDL	0.965	0.913	Graph Degree Linkage: Agglomerative Clustering on a Directed Graph	-
EnSC	0.969	0.941	Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering	-

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Image Clustering On Mnist Full | SOTA | HyperAI